Development of a predictive thermal model based on the equivalent source approach for SMAW welding of X70 steel pipes

Authors

DOI:

https://doi.org/10.15587/2706-5448.2026.352967

Keywords:

welding simulation, numerical design, SMAW welding, equivalent heat source, adjustments parameters

Abstract

The object of the research is the scientific approach for modeling thermal phenomena during welding operations in SMAW welding of pipelines. This model can be used to calculate changes in temperature fields as well as stresses and deformations.

Mastering welding processes requires an understanding of the various phenomena involved. This requires numerous tests to be carried out, which are very costly for manufacturers. The ideal solution would therefore be to develop predictive numerical models that would enable the behavior of assemblies to be analyzed. The SMAW process is used to fill a chamfer between two parts. It is therefore essential to define heat input, which can be described using the equivalent heat source approach the equivalent heat source approach. The difficulty in implementing this approach lies in estimating the various parameters of the model. To this end, it was proposed to develop a simple and robust approach, which consists of using the numerical design of experiments (NDE) method.

In this research, it was decided to select four parameters from the model (rsurf_sup, rsurf_inf, r0 and λ) and four objective functions characterizing the shape of the fusion zone (Lsup, Lm, Linf, H). Preliminary results show good agreement between the direct model and the dimensions recorded on the macrographic sections, with the exception of the width of the median side of the fusion zone (Lm), where there is a significant deviation of 11.4% between the measurements and the model. Furthermore, the NDE shows that rsurf_inf is the factor that most influences Lm. Adjusting the rsurf_inf factor by 0.5 from its value at the central point changes the Lm value from 3.25 mm to 3.09 mm. This adjustment optimizes the digital model by improving it and reducing the discrepancy between the simulation and the experiment for the Lm function from 11.4% to 1.2%. The results of this research make it possible to increase the reliability of petroleum facilities (pipeline assemblies). The scientific novelty of this research lies in the implementation of a simple and robust scientific approach for optimizing non-physical parameters (equivalent heat source parameters) in the modeling of welding processes.

Author Biographies

Adel Chouiter, Mentouri Brothers University Constantine1

PhD in Mechanical Engineering, HDR

Department of Mechanical Engineering

Laboratory Applied Sciences of Mechanics, Electromechanics and Materials (ASMEM)

Lyes Bidi, Mentouri Brothers University Constantine1

PhD in Mechanical Engineering, Professor

Laboratory Applied Sciences of Mechanics, Electromechanics and Materials (ASMEM)

Hadjer Bensiali, Mentouri Brothers University Constantine1

Doctor of Technical Sciences, PhD

Department of Transport Engineering

Laboratory of Transports and Environment Engineering

Rachid Chaib, MentouriBrothersUniversityConstantine1

Doctor of Technical Sciences, Professor

Department of Transport Engineering

Laboratory of Transports and Environment Engineering

Philippe Le Masson, University of Southern Brittany

PhD in Mechanical Engineering, Professor

C. HUYGENS Research Centre

References

  1. Goldak, J., Chakravarti, A., Bibby, M. (1984). A new finite element model for welding heat sources. Metallurgical Transactions B, 15 (2), 299–305. https://doi.org/10.1007/bf02667333
  2. Yu, D., Yang, C., Sun, Q., Dai, L., Wang, A., Xuan, H. (2023). Impact of process parameters on temperature and residual stress distribution of X80 pipe girth welds. International Journal of Pressure Vessels and Piping, 203, 104939. https://doi.org/10.1016/j.ijpvp.2023.104939
  3. Kong, F., Ma, J., Kovacevic, R. (2011). Numerical and experimental study of thermally induced residual stress in the hybrid laser–GMA welding process. Journal of Materials Processing Technology, 211 (6), 1102–1111. https://doi.org/10.1016/j.jmatprotec.2011.01.012
  4. Liu, S., Sun, J., Wei, F., Lu, M. (2018). Numerical simulation and experimental research on temperature and stress fields in TIG welding for plate of RAFM steel. Fusion Engineering and Design, 136, 690–693. https://doi.org/10.1016/j.fusengdes.2018.03.058
  5. Bidi, L., Mattei, S., Cicala, E., Andrzejewski, H., Le Masson, P., Schroeder, J. (2011). The use of exploratory experimental designs combined with thermal numerical modelling to obtain a predictive tool for hybrid laser/MIG welding and coating processes. Optics & Laser Technology, 43 (3), 537–545. https://doi.org/10.1016/j.optlastec.2010.07.011
  6. Zubairuddin, M., Albert, S. K., Vasudevan, M., Mahadevan, S., Chaudhari, V., Suri, V. K. (2017). Numerical simulation of multi-pass GTA welding of grade 91 steel. Journal of Manufacturing Processes, 27, 87–97. https://doi.org/10.1016/j.jmapro.2017.04.031
  7. Bendaoud, I., Matteï, S., Cicala, E., Tomashchuk, I., Andrzejewski, H., Sallamand, P. et al. (2014). The numerical simulation of heat transfer during a hybrid laser–MIG welding using equivalent heat source approach. Optics & Laser Technology, 56, 334–342. https://doi.org/10.1016/j.optlastec.2013.09.007
  8. Obeid, O., Alfano, G., Bahai, H., Jouhara, H. (2018). Numerical simulation of thermal and residual stress fields induced by lined pipe welding. Thermal Science and Engineering Progress, 5, 1–14. https://doi.org/10.1016/j.tsep.2017.10.005
  9. Goldak, J., Bibby, M., Moore, J., House, R., Patel, B. (1986). Computer modeling of heat flow in welds. Metallurgical Transactions B, 17 (3), 587–600. https://doi.org/10.1007/bf02670226
  10. Li, W., Yu, R., Huang, D., Wu, J., Wang, Y., Hu, T. et al. (2019). Numerical simulation of multi-layer rotating arc narrow gap MAG welding for medium steel plate. Journal of Manufacturing Processes, 45, 460–471. https://doi.org/10.1016/j.jmapro.2019.07.035
  11. Pichot, F., Danis, M., Lacoste, E., Danis, Y. (2013). Numerical definition of an equivalent GTAW heat source. Journal of Materials Processing Technology, 213 (7), 1241–1248. https://doi.org/10.1016/j.jmatprotec.2013.01.009
  12. Danis, Y., Lacoste, E., Arvieu, C. (2010). Numerical modeling of inconel 738LC deposition welding: Prediction of residual stress induced cracking. Journal of Materials Processing Technology, 210 (14), 2053–2061. https://doi.org/10.1016/j.jmatprotec.2010.07.027
  13. Farias, R. M., Teixeira, P. R. F., Vilarinho, L. O. (2021). An efficient computational approach for heat source optimization in numerical simulations of arc welding processes. Journal of Constructional Steel Research, 176, 106382. https://doi.org/10.1016/j.jcsr.2020.106382
  14. Lei, Y., Zhu, Q., Zhang, L., Gu, K., Ju, X. (2010). Simulation on the welding of CLAM steel. Fusion Engineering and Design, 85 (7–9), 1503–1507. https://doi.org/10.1016/j.fusengdes.2010.04.014
  15. Bag, S., Trivedi, A., De, A. (2009). Development of a finite element based heat transfer model for conduction mode laser spot welding process using an adaptive volumetric heat source. International Journal of Thermal Sciences, 48 (10), 1923–1931. https://doi.org/10.1016/j.ijthermalsci.2009.02.010
  16. Flint, T. F., Francis, J. A., Smith, M. C., Balakrishnan, J. (2017). Extension of the double-ellipsoidal heat source model to narrow-groove and keyhole weld configurations. Journal of Materials Processing Technology, 246, 123–135. https://doi.org/10.1016/j.jmatprotec.2017.02.002
  17. Chen, L., Mi, G., Zhang, X., Wang, C. (2019). Numerical and experimental investigation on microstructure and residual stress of multi-pass hybrid laser-arc welded 316L steel. Materials & Design, 168, 107653. https://doi.org/10.1016/j.matdes.2019.107653
  18. Farias, R. M., Teixeira, P. R. F., Vilarinho, L. O. (2022). Variable profile heat source models for numerical simulations of arc welding processes. International Journal of Thermal Sciences, 179, 107593. https://doi.org/10.1016/j.ijthermalsci.2022.107593
  19. Mondal, A. K., Kumar, B., Bag, S., Nirsanametla, Y., Biswas, P. (2021). Development of avocado shape heat source model for finite element based heat transfer analysis of high-velocity arc welding process. International Journal of Thermal Sciences, 166, 107005. https://doi.org/10.1016/j.ijthermalsci.2021.107005
  20. Belitzki, A., Marder, C., Huissel, A., Zaeh, M. F. (2016). Automated heat source calibration for the numerical simulation of laser beam welded components. Production Engineering, 10 (2), 129–136. https://doi.org/10.1007/s11740-016-0664-9
  21. Gannon, L., Liu, Y., Pegg, N., Smith, M. (2010). Effect of welding sequence on residual stress and distortion in flat-bar stiffened plates. Marine Structures, 23 (3), 385–404. https://doi.org/10.1016/j.marstruc.2010.05.002
  22. Azadi Moghaddam, M., Golmezergi, R., Kolahan, F. (2016). Multi-variable measurements and optimization of GMAW parameters for API-X42 steel alloy using a hybrid BPNN–PSO approach. Measurement, 92, 279–287. https://doi.org/10.1016/j.measurement.2016.05.049
  23. García-García, V., Reyes-Calderón, F., Camacho-Arriaga, J. C. (2016). Optimization of experimental temperature measurement in GTAW process by means of DoE technique and computational modeling. Measurement, 88, 297–309. https://doi.org/10.1016/j.measurement.2016.03.049
  24. Fu, G., Gu, J., Lourenco, M. I., Duan, M., Estefen, S. F. (2014). Parameter determination of double-ellipsoidal heat source model and its application in the multi-pass welding process. Ships and Offshore Structures, 10 (2), 204–217. https://doi.org/10.1080/17445302.2014.937059
  25. Bidi, L., Le Masson, P., Cicala, E., Primault, C. (2017). Experimental design method to the weld bead geometry optimization for hybrid laser-MAG welding in a narrow chamfer configuration. Optics & Laser Technology, 89, 114–125. https://doi.org/10.1016/j.optlastec.2016.09.046
  26. Wang, H., Woo, W., Kim, D.-K., Em, V., Lee, S. Y. (2018). Effect of chemical dilution and the number of weld layers on residual stresses in a multi-pass low-transformation-temperature weld. Materials & Design, 160, 384–394. https://doi.org/10.1016/j.matdes.2018.09.016
  27. Forouzan, M.R., Heidari, A., Golestaneh, S. J. (2009). FE simulation of submerged arc welding of API 5L-X70 straight seam oil and gas pipes. Journal of Computational Methods in Engineering, 28, 93–110 Available at: https://jcme.iut.ac.ir/article_3029_3925785f0e7afbb5933eb87d589edb33.pdf
  28. Bensiali, H., Bidi, L., Cicala, E., Le Masson, P., Chibani, M. E. B., Boulahlib, M. S. (2021). Effects of operating parameters on weld bead morphology with welding operations of API 5L X70 steel pipes by SMAW process. Welding in the World, 65 (6), 1119–1129. https://doi.org/10.1007/s40194-021-01085-4
  29. Bidi, L., Le Masson, P., Cicala, E. (2024). Influences of laser on the energy parameters of the electric arc in the case of laser-MIG hybrid welding. The International Journal of Advanced Manufacturing Technology, 131 (7–8), 4055–4069. https://doi.org/10.1007/s00170-024-13244-0
  30. Goupy, J. (2001). Introduction aux plans d’expériences. Paris: Dunod. Available at: https://iadji.com/wp-content/uploads/2020/08/Introduction-aux-Plans-dExperiences.pdf
  31. Montgomery, D. C. (1991). Design and analysis of experiments. Singapore: John Wiley & Sons. Available at: https://www.scribd.com/document/405637459/Douglas-C-Montgomery-Design-and-analysis-of-experiments-Wiley-1991-pdf?language_settings_changed=English
Development of a predictive thermal model based on the equivalent source approach for SMAW welding of X70 steel pipes

Downloads

Published

2026-02-28

How to Cite

Chouiter, A., Bidi, L., Bensiali, H., Chaib, R., & Le Masson, P. (2026). Development of a predictive thermal model based on the equivalent source approach for SMAW welding of X70 steel pipes. Technology Audit and Production Reserves, 1(1(87), 6–14. https://doi.org/10.15587/2706-5448.2026.352967

Issue

Vol. 1 No. 1(87) (2026): Industrial and technology systems

Section

Mechanical Engineering Technology

License

Copyright (c) 2026 Adel Chouiter, Lyes Bidi, Hadjer Bensiali, Rachid Chaib, Philippe Le Masson

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.